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Key Use Cases for Health Risk Assessments

Health risk assessments can determine the severity of illness, assist with predictive analytics, and promote chronic disease prevention.

Understanding an individual’s risk of disease is critical to providing the best quality of care. With health risk assessments (HRAs), also known as health risk appraisals, providers can collect patient data to identify potential risk factors and address concerns.

An HRA is an instrument that collects health information. The tool can be used to assist with predictive analytic efforts and chronic disease prevention. Additionally, data developed from HRA can help determine disease severity.

What is Health Risk Assessment?

HRAs began in the 1940s with prevention strategies against cervical cancer and heart disease. Researchers thought by incorporating treatment and prevention strategies, patients would experience better health outcomes than just treatment alone.

To collect patient information as part of an HRA, providers gather data through a questionnaire. The health data is then assessed, and clinicians provide personalized feedback regarding actions that patients can take to reduce health risks and prevent chronic disease.

HRAs include questions regarding social determinants of health in areas such as demographic characteristics, lifestyle behavior, emotional health, physical health, past medical history, and willingness to change health behaviors.

Aggregated HRA data can be used by medical professionals to understand the health risks facing a population and to improve provider resources. Additionally, organizations providing population health management services, including health plans or wellness providers, will use health risk assessment results to identify those who might benefit from care management.

Risk Assessment and Predictive Tools

HRA can also be used as a predictive tool for diseases. Through the questionnaires, physicians can identify specific factors that can contribute to severe illnesses.

Data collected from HRA can be used in developing risk prediction models using predictive analytics. With COVID-19 continuing to spread around the world, researchers have created different predictive models assessing patient risks.

A recent JAMA study identified the risk factors associated with severe COVID-19 cases in individuals using machine learning models and predictive analytics. The research included a retrospective cohort study of just short of 2 million US adults infected with COVID-19 and adult patients without the virus.

The data was gathered from 34 medical centers across the nation between January 1, 2020, and December 7, 2020. The patients were then stratified using the World Health Organization’s COVID-19 severity scale and demographic data and characteristics.

The patient data was then divided into 174,568 adults who tested positive for COVID-19 and a control group of 1,133,848 adults that tested negative. Of the adults that tested positive, 18.6 percent of them were hospitalized and 20.2 percent of those hospitalized had a severe clinical case.

The researchers concluded that demographic characteristics and comorbidities were tied to the higher clinical severity of COVID-19. By evaluating risk factors, researchers were able to predict patient outcomes.

Uses in Chronic Disease Prevention

While HRAs can be used to determine the severity of an illness, they can also be used in chronic disease prevention by identifying early warning signs. Before the condition develops, the patient’s clinician can make recommendations for preventative care, ideally stopping disease progression.

Currently, there are five chronic diseases that account for 75 percent of healthcare spending: cancer, cardiovascular disease, diabetes, obesity, and kidney disease. By identifying high-risk patients and risk factors with HRAs, medical professionals can recommend preventive care strategies to lessen the likelihood of chronic disease development.

The Centers for Disease Control and Prevention (CDC) released a report providing guidance on implementing patient-centered health risk assessments, follow-up activities, and monitoring of progress toward achieving health improvement goals.

According to the CDC, the goal of the report is to promote preventive care and disease management through HRAs, reduce health disparities, and improve health outcomes.

The CDC outlined in a multistep framework how to provide patient-centered HRAs, including:

  • Balance comprehensiveness of assessment with provider and patient burden
  • Build upon high priority questions
  • Use person-centered and culturally appropriate processes
  • Comply with all federal laws and regulations regarding access for persons with disabilities
  • Use a shared decision-making process

Additionally, providers should continue to follow up with patients, monitor their conditions, and keep updated EHRs. By conducting HRAs, providers can catch early warning signs of chronic disease and take preventative measures.

With HRAs, organizations can determine disease severity, create predictive models, and engage in chronic disease prevention. HRAs are an important tool in providing improved patient care and population health management.

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